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Purpose: This paper aims to develop an algorithm to pretest an industrial portfolio on a new scale. Portfolios include complex and uncertain projects at the front-end phase. The study, therefore, proposes a procedure that helps decision-makers to handle various complex projects and defines a common scale applicable to various kinds of industrial projects. Design/methodology/approach: Decision-makers can employ the preference algorithm to reach a common understanding. To this end, the current paper posits the organization of criteria in various project sets. A sexagesimal scale is developed based on project complexity and its ability to achieve broad impact, both these factors being gauged on a five-point scale of user-friendly numberings. Findings: The proposed algorithm shows the equivalence of industrial projects in different fields. Also, the algorithm articulates the status in terms of uncertainty, complexity, risk, and value of projects. The connections between decision-makers and criteria operate on the basis of the foreseen complexity, risk, and value. It can be said that this study exemplifies and visualizes the portfolio and criteria relationship. Research limitations/implications: The procedure covers contingency exercises at the front-end phase of a portfolio and supports decisions. However, updated information can change support positions. Originality/value: The paper presents original scoring guidance for portfolio complexity on a new scale. The scaling and scoring are adjustable and calibrated using the proposed sexagesimal system. It presents an original classification of project risk and value. The main contribution is the presented algorithm which can be used to pretest industrial portfolios composed of projects that vary in both size and context. [ABSTRACT FROM AUTHOR]

Purpose: This paper aims to focus on the inclusion of the frequency behavior of grounding system effect on surge arrester (SA) model parameters' estimation. Design/methodology/approach: The grounding system impedance and its frequency behavior are the factors that have influence on the SA performance. Up to now, the grounding system impedance effect and the frequency behavior of the soil parameters have not been studied for the estimation of the parameters of the SA frequency-dependent model. In this paper, the grounding system's influence on the SA dynamic model has been simulated for rod- and counterpoise-shaped electrodes. Particle swarm optimization with a grey wolf optimization algorithm has been implemented as an optimization algorithm to adjust the parameters of the SA dynamic model. Findings: The results show that the frequency behavior of the grounding impedance and soil electrical parameters can impress the optimum parameters of the SA frequency-dependent model and should be considered for more reliable results. Also, the results evidence that the proposed optimization method provides more accurate results compared to other optimization methods. Originality/value: To the best of the authors' knowledge, this work is one of the first attempts to investigate the effect of frequency grounding system on SA frequency-dependent model parameters. [ABSTRACT FROM AUTHOR]

Purpose: A novel asynchronous network-based model is proposed in this paper for the sentiment analysis of online public opinions. This new model provides a new approach to analyze the evolution characteristics of online public opinion sentiments in complex environment. Design/methodology/approach: Firstly, a new sentiment analysis model is proposed based on the asynchronous network theory. Then the graphical evaluation and review technique is employed and extended to design the model-based sentiment analysis algorithms. Finally, simulations and real-world case studies are given to show the effectiveness of the proposed model. Findings: The dynamics of online public opinion sentiments are determined by both personal preferences to certain topics and the complex interactive influences of environmental factors. The application of appropriate quantitative models can improve the prediction of public opinion sentiment. Practical implications: The proposed model-based algorithms provide simple but effective ways to explore the complex dynamics of online public opinions. Case studies highlight the role of government agencies in shaping sentiments of public opinions on social topics. Originality/value: This paper proposes a new asynchronous network model for the dynamic sentiment analysis of online public opinions. It extends the previous static models and provides a new way to extract opinion evolution patterns in complex environment. Applications of the proposed model provide some new insights into the online public opinion management. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this study is to analyze direct current (DC) drive stability, including parameter uncertainty and perturbation in the feedback loop, by computing disk margins. Design/methodology/approach: Although the closed-loop stability analysis of a DC drive has been presented well in the referenced papers, the effect of parameter uncertainty and perturbation in the feedback loop has not yet been discussed well. In this study, the conventional and disk-based stability margins were measured and compared for the nominal parameters of the DC drive. Subsequently, the smallest disk-based margins that destabilize the feedback loop for a given perturbation are computed and compared with normal disk margins. Findings: The disk-based margin offered by the DC drive controlled by the JAYA-PID controller is disk gain margins (DGM) = 8.41 dB and disk phase margin (DPM) = 48.410 and the smallest disk-based margin offered is DGM = 1.51 dB and DPM = 9.950. In addition, the effect of the modeled uncertainty on the disk stability margins was analyzed, and it was observed that the maximum allowable parameter uncertainty with the JAYA controller was 73% of its nominal parameters. The simulation results were validated using an experimental testbed. Originality/value: This research work is not published anywhere else. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this study is to propose a new consumer value segmentation method for low-dimensional dense market datasets to quickly detect and cluster the most profitable customers for the enterprises. Design/methodology/approach: In this study, the comprehensive segmentation bases (CSB) with richer meanings were obtained by introducing the weighted recency-frequency-monetary (RFM) model into the common segmentation bases (SB). Further, a new market segmentation method, the CSB-MBK algorithm was proposed by integrating the CSB model and the mini-batch k-means (MBK) clustering algorithm. Findings: The results show that our proposed CSB model can reflect consumers' contributions to a market, as well as improve the clustering performance. Moreover, the proposed CSB-MBK algorithm is demonstrably superior to the SB-MBK, CSB-KMA and CSB-Chameleon algorithms with respect to the Silhouette Coefficient (SC), the Calinski-Harabasz (CH) Index , the average running time and superior to the SB-MBK, RFM-MBK and WRFM-MBK algorithms in terms of the inter-market value and characteristic differentiation. Practical implications: This paper provides a tool for decision-makers and marketers to segment a market quickly, which can help them grasp consumers' activity, loyalty, purchasing power and other characteristics in a target market timely and achieve the precision marketing. Originality/value: This study is the first to introduce the CSB-MBK algorithm for identifying valuable customers through the comprehensive consideration of the clustering quality, consumer value and segmentation speed. Moreover, the CSB-MBK algorithm can be considered for applications in other markets. [ABSTRACT FROM AUTHOR]

Purpose: This paper aims to deal with the optimal shape design of a class of permanent magnet motors by minimizing multiple objectives according to an original interpretation of Pareto optimality. The proposed method solves a many-objective problems characterized by five objective functions and five design variables with evolution strategy algorithms, classically used for single- and multi-objective (two objective functions) optimization problems. Design/methodology/approach: Two approaches are proposed in the paper: the All-Objectives (AO) and the Many-Objectives (MO) optimization approach. The former is based on a single-objective optimization of a preference function, i.e. a normalized weighted sum. In contrast, in the MO a multi-objective optimization algorithm is applied to the minimization of a weight-free preference function and simultaneously to a maximization of the distance of the current solution from the prototype. The optimizations are based on an equivalent circuit model of the Permanent Magnet (PM) motor, but the results are assessed by means of finite element analyses (FEAs). Findings: An extensive study of the solutions obtained by means of the different optimization approaches is provided by means of post-processing analyses. Both the approaches find non-dominated solutions with respect to the prototype that are substantially improving the initial solution. The points of strength along with the weakness points of each solution with respect to the prototype are analysed in depth. Practical implications: The paper gives a good guide to the designers of electric motors, focussed on a shape design optimization. Originality/value: Considering simultaneously five objective functions in an automated optimal design procedure is challenging. The proposed approach, based on a well-known and established optimization algorithm, but exploiting a new concept of degree of conflict, can lead to new results in the field of automated optimal design in a many-objective context. [ABSTRACT FROM AUTHOR]

Purpose: Monitoring and diagnosis of fault cases for squirrel cage induction motors can be implemented using the multiple coupled circuit model. However, the identification of the associated model parameters for a specific machine is problematic. Up to now, the main options are measurement and test procedures or the use of finite element method analyses. However, these approaches are very costly and not suitable for use in an industrial application. The purpose of this paper is a practical parameter identification based on optimization methods and a comparison of different algorithms for this task. Design/methodology/approach: Population-based metaheuristics are used to determine the parameters for the multiple coupled circuit model. For this purpose, a search space for the required parameters is defined without an elaborate analytical approach. Subsequently, a genetic algorithm, the differential evolution algorithm and particle swarm optimization are tested and compared. The algorithms use the weighted mean squared error (MSE) between the real measured data of stator currents as well as speed and the simulation results of the model as a fitness function. Findings: The results of the parameter identification show that the applied methodology generally works and all three optimization algorithms fulfill the task. The differential evolution algorithm performs best, with a weighted MSE of 2.62, the lowest error after 1,000 simulations. In addition, this algorithm achieves the lowest overall error of all algorithms after only 740 simulations. The determined parameters do not completely match the parameters of the real machine, but still result in a very good reproduction of the dynamic behavior of the induction motor with squirrel cage. Originality/value: The value of the presented method lies in the application of condition-based maintenance of electric drives in the industry, which is performed based on the multiple coupled circuit model. With a parameterized model, various healthy as well as faulty states can be calculated and thus, in the future, monitoring and diagnosis of faults of the respective motor can be performed. Essential for this, however, are the parameters adapted to the respective machine. With the described method, an automated parameter identification can be realized without great effort as a basis for an intelligent and condition-oriented maintenance. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this study is to further advance the multiple space/time subdomain framework with model reduction. Existing linear multistep (LMS) methods that are second-order time accurate, and useful for practical applications, have a significant limitation. They do not account for separable controllable numerical dissipation of the primary variables. Furthermore, they have little or no significant choices of altogether different algorithms that can be integrated in a single analysis to mitigate numerical oscillations that may occur. In lieu of such limitations, under the generalized single-step single-solve (GS4) umbrella, several of the deficiencies are circumvented. Design/methodology/approach: The GS4 framework encompasses a wide variety of LMS schemes that are all second-order time accurate and offers controllable numerical dissipation. Unlike existing state-of-art, the present framework permits implicit–implicit and implicit–explicit coupling of algorithms via differential algebraic equations (DAE). As further advancement, this study embeds proper orthogonal decomposition (POD) to further reduce model sizes. This study also uses an iterative convergence check in acquiring sufficient snapshot data to adequately capture the physics to prescribed accuracy requirements. Simple linear/nonlinear transient numerical examples are presented to provide proof of concept. Findings: The present DAE-GS4-POD framework has the flexibility of using different spatial methods and different time integration algorithms in altogether different subdomains in conjunction with the POD to advance and improve the computational efficiency. Originality/value: The novelty of this paper is the addition of reduced order modeling features, how it applies to the previous DAE-GS4 framework and the improvement of the computational efficiency. The proposed framework/tool kit provides all the needed flexibility, robustness and adaptability for engineering computations. [ABSTRACT FROM AUTHOR]

Purpose: This paper aims to propose a new assessment system module for handling the comprehensive answers written through the answer interface. Design/methodology/approach: The working principle is under three major phases: Preliminary semantic processing: In the pre-processing work, the keywords are extracted for each answer given by the course instructor. In fact, this answer is actually considered as the key to evaluating the answers written by the e-learners. Keyword and semantic processing of e-learners for hierarchical clustering-based ontology construction: For each answer given by each student, the keywords and the semantic information are extracted and clustered (hierarchical clustering) using a new improved rider optimization algorithm known as Rider with Randomized Overtaker Update (RR-OU). Ontology matching evaluation: Once the ontology structures are completed, a new alignment procedure is used to find out the similarity between two different documents. Moreover, the objects defined in this work focuses on "how exactly the matching process is done for evaluating the document." Finally, the e-learners are classified based on their grades. Findings: On observing the outcomes, the proposed model shows less relative mean squared error measure when weights were (0.5, 0, 0.5), and it was 71.78% and 16.92% better than the error values attained for (0, 0.5, 0.5) and (0.5, 0.5, 0). On examining the outcomes, the values of error attained for (1, 0, 0) were found to be lower than the values when weights were (0, 0, 1) and (0, 1, 0). Here, the mean absolute error (MAE) measure for weight (1, 0, 0) was 33.99% and 51.52% better than the MAE value for weights (0, 0, 1) and (0, 1, 0). On analyzing the overall error analysis, the mean absolute percentage error of the implemented RR-OU model was 3.74% and 56.53% better than k-means and collaborative filtering + Onto + sequential pattern mining models, respectively. Originality/value: This paper adopts the latest optimization algorithm called RR-OU for proposing a new assessment system module for handling the comprehensive answers written through the answer interface. To the best of the authors' knowledge, this is the first work that uses RR-OU-based optimization for developing a new ontology alignment-based online assessment of e-learners. [ABSTRACT FROM AUTHOR]

Purpose: Accurate foreign tourist arrivals forecasting can help public and private sectors to formulate scientific tourism planning and improve the allocation efficiency of tourism resources. This paper aims to address the problem of low prediction accuracy of Chinese inbound tourism demand caused by the lack of valid historical data. Design/methodology/approach: A novel hybrid Chinese inbound tourism demand forecasting model combining fractional non-homogenous discrete grey model and firefly algorithm is constructed. In the proposed model, all adjustable parameters of the fractional non-homogenous discrete grey model are optimized simultaneously by the firefly algorithm. Findings: The data sets of annual foreign tourist arrivals to China are used to verify the validity of the proposed model. Experimental results show that the proposed method is effective and can be used as a useful predictor for the prediction of Chinese inbound tourism demand. Originality/value: The method proposed in this paper is effective and can be used as a feasible approach for forecasting the development trend of Chinese inbound tourism. [ABSTRACT FROM AUTHOR]

Purpose: This paper aims to apply grey wolf optimizer (GWO) algorithm for steady state analysis of self-excited induction generators (SEIGs) supplying isolated loads. Design/methodology/approach: Taking the equivalent circuit of SEIG, the impedances representing the stator, rotor and the connected load are reduced to a single loop impedance in terms of the unknown frequency, magnetizing reactance and core loss resistance for the given rotor speed. This loop impedance is taken as the objective function and minimized using GWO to solve for the unknown parameters. By including the value of the desired voltage as a constraint, the formulated objective function is also extended for estimating the required excitation capacitance. Findings: The experimental results obtained on a three phase 415 V, 3.5 kW SEIG and the corresponding predetermined performance characteristics agree closely, thereby validating the proposed GWO method. Moreover, a comparative study of GWO with genetic algorithm and particle swarm optimization techniques reveals that GWO exhibits much quicker convergence of the objective function. Originality/value: The important contributions of this paper are as follows: for the first time, GWO has been introduced for the SEIG performance predetermination and computation of the excitation capacitance for attaining the desired terminal voltage for the given load and speed; the predicted performance accuracy is improved by considering the variable core loss of the SEIG; and GWO does not require derivations of lengthy equations for calculating the SEIG performance. [ABSTRACT FROM AUTHOR]

Purpose: In general, cloud computing is a model of on-demand business computing that grants a convenient access to shared configurable resources on the internet. With the increment of workload and difficulty of tasks that are submitted by cloud consumers; "how to complete these tasks effectively and rapidly with limited cloud resources?" is becoming a challenging question. The major point of a task scheduling approach is to identify a trade-off among user needs and resource utilization. However, tasks that are submitted by varied users might have diverse needs of computing time, memory space, data traffic, response time, etc. This paper aims to proposes a new way of task scheduling. Design/methodology/approach: To make the workflow completion in an efficient way and to reduce the cost and flow time, this paper proposes a new way of task scheduling. Here, a self-adaptive fruit fly optimization algorithm (SA-FFOA) is used for scheduling the workflow. The proposed multiple workflow scheduling model compares its efficiency over conventional methods in terms of analysis such as performance analysis, convergence analysis and statistical analysis. From the outcome of the analysis, the betterment of the proposed approach is proven with effective workflow scheduling. Findings: The proposed algorithm is more superior regarding flow time with the minimum value, and the proposed model is enhanced over FFOA by 0.23%, differential evolution by 2.48%, artificial bee colony (ABC) by 2.85%, particle swarm optimization (PSO) by 2.46%, genetic algorithm (GA) by 2.33% and expected time to compute (ETC) by 2.56%. While analyzing the make span case, the proposed algorithm is 0.28%, 0.15%, 0.38%, 0.20%, 0.21% and 0.29% better than the conventional methods such as FFOA, DE, ABC, PSO, GA and ETC, respectively. Moreover, the proposed model has attained less cost, which is 2.14% better than FFOA, 2.32% better than DE, 3.53% better than ABC, 2.43% better than PSO, 2.07% better than GA and 2.90% better than ETC, respectively. Originality/value: This paper presents a new way of task scheduling for making the workflow completion in an efficient way and for reducing the cost and flow time. This is the first paper uses SA-FFOA for scheduling the workflow. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this paper is to improve transient response and dynamic performance of automatic voltage regulator (AVR). Design/methodology/approach: This paper proposes a novel fractional order proportional–integral–derivative plus derivative (PIλDµDµ2) controller called FOPIDD for AVR system. The FOPIDD controller has seven optimization parameters and the equilibrium optimizer algorithm is used for tuning of controller parameters. The utilized objective function is widely preferred in AVR systems and consists of transient response characteristics. Findings: In this study, results of AVR system controlled by FOPIDD is compared with results of proportional–integral–derivative (PID), proportional–integral–derivative acceleration, PID plus second order derivative and fractional order PID controllers. FOPIDD outperforms compared controllers in terms of transient response criteria such as settling time, rise time and overshoot. Then, the frequency domain analysis is performed for the AVR system with FOPIDD controller, and the results are found satisfactory. In addition, robustness test is realized for evaluating performance of FOPIDD controller in perturbed system parameters. In robustness test, FOPIDD controller shows superior control performance. Originality/value: The FOPIDD controller is introduced for the first time to improve the control performance of the AVR system. The proposed FOPIDD controller has shown superior performance on AVR systems because of having seven optimization parameters and being fractional order based. [ABSTRACT FROM AUTHOR]

Purpose: This paper aims to present a modified MEC algorithm for demagnetization modeling of the PM motor. One of the major issues that the designers of the permanent magnet (PM) motors are faced with is the demagnetization of magnets because of high temperatures and armature reaction. Demagnetization will weaken the magnetic properties of the magnet and lead to a reduction in the performance of the motor. Therefore, it is essential to provide appropriate methods for modeling this phenomenon. One of these methods that has a compromise between accuracy and time consumption is the magnetic equivalent circuit (MEC). In this paper, the MEC method is used for modeling the demagnetization phenomenon for the newly introduced ring winding axial flux PM (RWAFPM) motor. The proposed algorithm can take the demagnetization into account through a time-stepping model and also correct the value of the knee point flux density. Design/methodology/approach: The modified MEC method is used for demagnetization modeling. The modified algorithm can take into account demagnetization and also renew the knee point at each step to increase the accuracy of the modeling. In addition, the proposed algorithm has a very high and fast execution speed so that the computation time of the MEC algorithm compared to the FEM model is reduced from 3 h to 35 s. In this case, the simulations have been performed on a core i5@ 2.3 GHz/8GB computer. The FEM model is used to verify the validity of the MEC results. Findings: The obtained results show that at the high temperature, RWAFPM motor is severely vulnerable to demagnetization. At the temperature of 140°C, the demagnetization rate of 35% has occurred. So, it is necessary to use the high-temperature magnet in this motor or modify the motor structure in terms of demagnetization tolerant capability. Originality/value: The RWAFPM motor is introduced for use in ship propulsion and traction systems. For this reason, an accurate estimation of demagnetization tolerant of this motor in different working conditions can show the strengths and weaknesses of this structure. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this paper is to introduce two new (3 + 1)-dimensional Boiti–Leon–Manna–Pempinelli (BLMP) equations, the first with constant coefficients and the other with time-dependent coefficients. The author obtains multiple soliton solutions and multiple complex soliton solutions for the two developed models. Design/methodology/approach: The newly developed models with constant coefficients and with time-dependent coefficients have been handled by using the simplified Hirota's method. The author also uses the complex Hirota's criteria for deriving multiple complex soliton solutions. Findings: The two developed BLMP models exhibit complete integrability for any constant coefficient and any analytic time-dependent coefficients by investigating the compatibility conditions for each developed model. Research limitations/implications: The paper presents an efficient algorithm for handling integrable equations with constant and analytic time-dependent coefficients. Practical implications: The paper presents two new integrable equations with a variety of coefficients. The author showed that integrable equations with constant and time-dependent coefficients give real and complex soliton solutions. Social implications: The paper presents useful algorithms for finding and studying integrable equations with constant and time-dependent coefficients. Originality/value: The paper presents an original work with a variety of useful findings. [ABSTRACT FROM AUTHOR]

Purpose: Traditional switching harmonic suppressor design methods require domain experts to adjust design parameters due to various complex performance requirements and practical limitations in switching ripple suppressor designs. The purpose of this paper is to present a method for filter parameter design. Design/methodology/approach: An improved non-dominated sorting genetic algorithm II (NSGA II) was used in the inductor-capacitor-inductor (LCL) filter design to find the optimal design parameters, and a method was proposed to handle the constraints by transforming the them into decision variables. Findings: The performance of the proposed algorithm in parameter designing was verified by simulation on MATLAB and experimental results on hardware-in-the-loop plat-form with StarSim software. The results indicate that the optimization algorithm has a better effect than the traditional expert parameters on each optimization index, especially on the switching harmonic suppression. Originality/value: The paper presents an improved multi-objective optimization algorithm with ingenious constraints handing to obtain better filter parameters and reduces switching harmonics. [ABSTRACT FROM AUTHOR]

Purpose: This paper aims to propose an enhanced algorithm and used to decision-making that specifically focuses on the choice of a domain in the calculation of degree of greyness according to the principle of grey numbers operation. The domain means the emerging background of interval grey numbers, it is vital for the operational mechanism of such interval grey numbers. However, the criteria of selection of domain always remain same that is not only for the calculated grey numbers but also for the resultant grey numbers, which can be assumed as unrealistic up to a certain extent. Design/methodology/approach: The existence of interval grey number operation based on kernel and the degree of greyness containing two calculation aspects, which are kernel and the degree of greyness. For the degree of greyness, it includes concepts of domain and calculation of the domain. The concepts of a domain are defined. The enhanced algorithm is also comprised of four deductive theorems and eight rules that are linked to the properties of the enhanced algorithm of the interval grey numbers based on the kernel and the degree of greyness. Findings: Aiming to improve the algorithm of the degree of greyness for interval grey numbers, based on the variation of domain in the operation process, the degree of greyness of the operation result is defined in this paper, and the specific expressions for algebraic operations are given, which is relevant to the kernel, the degree of greyness and the domain. Then, these expressions are used to the algorithm of interval grey numbers based on the kernel and the degree of greyness, improving the accuracy of the operation results. Originality/value: The enhanced algorithm in this paper can effectively reduce the loss of information in the operation process, so as to avoid the situation where the decision values are the same and scientific decisions cannot be made during the grey evaluation and decision-making process. [ABSTRACT FROM AUTHOR]

Purpose: Pressure-based methods have been demonstrated to be powerful for solving many practical problems in engineering. In many pressure-based methods, inner iterative processes are proposed to get efficient solutions. However, the number of inner iterations is set empirically and kept fixed during the whole computation for different problems, which is overestimated in some computations but underestimated in other computations. This paper aims to develop an algorithm with adaptive inner iteration processes for steady and unsteady incompressible flows. Design/methodology/approach: In this work, with the use of two different criteria in two inner iterative processes, a mechanism is proposed to control inner iteration processes to make the number of inner iterations vary during computing according to different problems. By doing so, adaptive inner iteration processes can be achieved. Findings: The adaptive inner iterative algorithm is verified to be valid by solving classic steady and unsteady incompressible problems. Results show that the adaptive inner iteration algorithm works more efficient than the fixed inner iteration one. Originality/value: The algorithm with adaptive inner iteration processes is first proposed in this paper. As the mechanism for controlling inner iteration processes is based on physical meaning and the feature of iterative calculations, it can be used in any methods where there exist inner iteration processes. It is not limited for incompressible flows. The performance of the adaptive inner iteration processes in compressible flows is conducted in a further study. [ABSTRACT FROM AUTHOR]

Purpose: Big data are indispensable in scientific endeavours ranging from nuclear research to climate studies. However, there is a growing misperception that congeries of data can be easily reconstructed into competitive business insights. Such notions have been encouraged by a plethora of mainstream techno-utopian forecasts. Design/methodology/approach: This paper investigated such claims and related big data developments, including its "systems-first" and oligopolistic orientations. Due to the paucity of current scholarship on an admittedly pessimistic topic, the paper studied contrarian developments in the industry by relying on secondary data. The study of experts and scholars; industrial trends; and discrepancies and critical gaps in the mainstream data narrative were sourced to prognosticate the likely trajectory of many data giants. Findings: A key finding was that the big data industry faces an untenable market bubble worth trillions of dollars. This will have severe consequences for common digital access and social stability worldwide. Evidence presented also suggests that the data industrial complex may undergo a function creep by facilitating a transition from surveillance capitalism to surveillance society. Research limitations/implications: Primary data for a study of this nature may take years to materialize. This is a "first-pass" study that seeks to illuminate latent dangers facing the big data/AI sector. There is a paucity of scholarly study that even remotely touches on this topic. Therefore, supporting arguments was sourced from contemporary reports and expert study (secondary data). Practical implications: As control of data may have geostrategic implications, balkanization of the wired ecosystem may be underway with Russia and China leading the way. Future superpowers may be defined by the way they handle data. The concentration of data in fewer hands may also affect citizen innovation. Social implications: A break-down of the data industrial complex may lead to social mayhem as the monetization of presently free software, blogs and social media platforms may be unfeasible. Originality/value: This topic has hardly been explored due to the novelty of big data, its applications and the daily hype over its potentials. This paper boldly describes dark countercurrents in the industry. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this paper is to develop a hybrid algorithm, which is a blend of auto-regressive integral moving average (ARIMA) and multilayer perceptron (MLP) for addressing the non-linearity of the load time series. Design/methodology/approach: Short-term load forecasting is a complex process as the nature of the load-time series data is highly nonlinear. So, only ARIMA-based load forecasting will not provide accurate results. Hence, ARIMA is combined with MLP, a deep learning approach that models the resultant data from ARIMA and processes them further for Modelling the non-linearity. Findings: The proposed hybrid approach detects the residuals of the ARIMA, a linear statistical technique and models these residuals with MLP neural network. As the non-linearity of the load time series is approximated in this error modeling process, the proposed approach produces accurate forecasting results of the hourly loads. Originality/value: The effectiveness of the proposed approach is tested in the laboratory with the real load data of a metropolitan city from South India. The performance of the proposed hybrid approach is compared with the conventional methods based on the metrics such as mean absolute percentage error and root mean square error. The comparative results show that the proposed prediction strategy outperforms the other hybrid methods in terms of accuracy. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of the paper is to develop a simple, efficient and robust power flow (PF) method for ill-conditioned distribution networks (DNs). Design/methodology/approach: It first formulates the PF problem as an optimization problem of minimizing the node power mismatches, while treating the corrections of node voltages as problem variables and then uses soccer game optimization (SGO), an artificial intelligent algorithm simulating the behavior of soccer game players in scoring goals, in solving the formulated PF problem. Findings: It studies the performances of the developed method on four standard test DNs and exhibits that the method is superior in respect of accuracy, robustness and computational speed than those of existing methods. Originality/value: It suggests a novel and new PF method using SGO and portrays that the proposed method is as accurate as any other PF method, robust like non-Newton type of PF methods and faster than Newton type of PF methods. [ABSTRACT FROM AUTHOR]

Purpose: This paper aims to omit the difficulties of directly finding the periodic steady-state solutions for electromagnetic devices described by circuit models. Design/methodology/approach: Determine the discrete integral operator of periodic functions and develop an iterative algorithm determining steady-state solutions by a multiplication of matrices only. Findings: An alternative method to creating finite-difference relations directly determining steady-state solutions in the time domain. Research limitations/implications: Reduction of software and hardware requirements for determining steady-states of electromagnetic. Practical implications: A unified approach for directly finding steady-state solutions for ordinary nonlinear differential equations presented in the normal form. Originality/value: Eliminate the necessity of solving high-order finite-difference equations for steady-state analysis of electromagnetic devices described by circuit models. [ABSTRACT FROM AUTHOR]

Purpose: Purpose of this paper are Real power loss reduction, voltage stability enhancement and minimization of Voltage deviation. Design/methodology/approach: In HLG approach as per Henry gas law sum of gas dissolved in the liquid is directly proportional to the partial pressure on above the liquid. Gas dissolving in the liquid which based on Henry gas law is main concept to formulate the proposed algorithm. Populations are divided into groups and all the groups possess the similar Henry constant value. Exploration and exploitation has been balanced effectively. Ranking and position of the worst agents is done in order to avoid the local optima. Then in this work Mobula alfredi optimization (MAO) algorithm is projected to solve optimal reactive power problem. Foraging actions of Mobula alfredi has been imitated to design the algorithm. String foraging, twister foraging and backward roll foraging are mathematically formulated to solve the problem. In the entire exploration space the Mobula alfredi has been forced to discover new regions by assigning capricious position. Through this approach, exploration competence of the algorithm has been improved. In all iterations, the position of the Mobula alfredi has been updated and replaced with the most excellent solution found so far. Exploration and exploitation capabilities have been maintained sequentially. Then in this work balanced condition algorithm (BCA) is projected to solve optimal reactive power problem. Proposed BCA approach based on the conception in physics- on the subject of the mass; incoming, exit and producing in the control volume. Preliminary population has been created based on the dimensions and number of particles and it initialized capriciously in the exploration space with minimum and maximum concentration. Production control parameter and Production probability utilized to control the exploration and exploitation. Findings: Proposed Henry's Law based -soluble gas optimization (HLG) algorithm, Mobula alfredi optimization (MAO) algorithm and BCA are evaluated in IEEE 30 bus system with L-index (Voltage stability) and also tested in standard IEEE 14, 30, 57, 118, 300 bus test systems without L- index. Real power loss minimization, voltage deviation minimization, and voltage stability index enhancement has been attained. Originality/value: For the first time Henry's Law based -soluble gas optimization (HLG) algorithm, Mobula alfredi optimization (MAO) algorithm and BCA is projected to solve the power loss reduction problem. [ABSTRACT FROM AUTHOR]

Purpose This paper aims to present a high-order algorithm implemented with the modal spectral element method and simulations of three-dimensional thermal convective flows by using the full viscous dissipation function in the energy equation. Three benchmark problems were solved to validate the algorithm with exact or theoretical solutions. The heated rotating sphere at different temperatures inside a cold planar Poiseuille flow was simulated parametrically at varied angular velocities with positive and negative rotations.Design/methodology/approach The fourth-order stiffly stable schemes were implemented and tested for time integration. To provide the hp-refinement and spatial resolution enhancement, a modal spectral element method using hierarchical basis functions was used to solve governing equations in a three-dimensional space.Findings It was found that the direction of rotation of the heated sphere has totally different effects on drag, lateral force and torque evaluated on surfaces of the sphere and walls. It was further concluded that the angular velocity of the heated sphere has more influence on the wall normal velocity gradient than on the wall normal temperature gradients and therefore, more influence on the viscous dissipation than on the thermal dissipation.Research limitations/implications This paper concerns incompressible fluid flow at constant properties with up to medium temperature variations in the absence of thermal radiation and ignoring the pressure work.Practical implications This paper contributes a viable high-order algorithm in time and space for modeling convective heat transfer involving an internal heated rotating sphere with the effect of viscous heating.Social implications Results of this paper could provide reference for related topics such as enhanced heat transfer forced convection involving rotating spheres and viscous thermal effect.Originality/value The merits include resolving viscous dissipation and thermal diffusion in stationary and rotating boundary layers with both h- and p-type refinements, visualizing the viscous heating effect with the full viscous dissipation function in the energy equation and modeling the forced advection around a rotating sphere with varied positive and negative angular velocities subject to a shear flow. [ABSTRACT FROM AUTHOR]

Purpose: To design, control and evaluate photovoltaic (PV) systems, an accurate model is required. Accuracy of PV models depends on model parameters. This study aims to use a new algorithm called improved social spider algorithm (ISSA) to detect model parameters. Design/methodology/approach: To improve performance of social spider algorithm (SSA), an elimination period is added. In addition, at the beginning of each period, a certain number of the worst solutions are replaced by new solutions in the search space. This allows the particles to find new paths to get the best solution. Findings: In this paper, ISSA is used to estimate parameters of single-diode and double-diode models. In addition, effect of irradiation and temperature on I–V curves of PV modules is studied. For this purpose, two different modules called multi-crystalline (KC200GT) module and polycrystalline (SW255) are used. It should be noted that to challenge the performance of the proposed algorithm, it has been used to identify the parameters of a type of widely used module of fuel cell called proton exchange membrane fuel cell. Finally, comparing and analyzing of ISSA results with other similar methods shows the superiority of the presented method. Originality/value: Changes in the spider's movement process in the SSA toward the desired response have improved the algorithm's performance. Higher accuracy and convergence rate, skipping local minimums, global search ability and search in a limited space can be mentioned as some advantages of this modified method compared to classic SSA. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this paper is to suggest a general numerical algorithm for nonlinear problems by the variational iteration method (VIM). Design/methodology/approach: Firstly, the Laplace transform technique is used to reconstruct the variational iteration algorithm-II. Secondly, its convergence is strictly proved. Thirdly, the numerical steps for the algorithm is given. Finally, some examples are given to show the solution process and the effectiveness of the method. Findings: No variational theory is needed to construct the numerical algorithm, and the incorporation of the Laplace method into the VIM makes the solution process much simpler. Originality/value: A universal iteration formulation is suggested for nonlinear problems. The VIM cleans up the numerical road to differential equations. [ABSTRACT FROM AUTHOR]

Purpose The purpose of this paper is to highlight the advantages of a simplified algorithm to solve the problem of heat and mass transfer in porous medium by reducing the number of partial differential equations from four to three.Design/methodology/approach The approach of the present paper is to develop a simplified algorithm to reduce the number of equations involved in conjugate heat transfer in porous medium.Findings Developed algorithm/method has many advantages over conventional method of solution for conjugate heat transfer in porous medium.Research limitations/implications The current work is applicable to conjugate heat transfer problem.Practical implications The developed algorithm is useful in reducing the number of equations to be solved, thus reducing the computational resources required.Originality/value Development of simplified algorithm and comparison with conventional method. [ABSTRACT FROM AUTHOR]

Purpose: This paper aims to investigate the thermal performance involving larger heating rate, targeted heating, heating with least non-uniformity of the spatial distribution of temperature and larger penetration of heating within samples vs shapes of samples (circle, square and triangular). Design/methodology/approach: Galerkin finite element method (GFEM) with adaptive meshing in a composite domain (free space and sample) is used in an in-house computer code. The finite element meshing is done in a composite domain involving triangle embedded within a semicircular hypothetical domain. The comparison of heating pattern is done for various shapes of samples involving identical cross-sectional area. Test cases reveal that triangular samples can induce larger penetration of heat and multiple heating fronts. A representative material (beef) with high dielectric loss corresponding to larger microwave power or heat absorption in contrast to low lossy samples is considered for the current study. The average power absorption within lossy samples has been computed using the spatial distribution and finite element basis sets. Four regimes have been selected based on various local maxima of the average power for detailed investigation. These regimes are selected based on thin, thick and intermediate limits of the sample size corresponding to the constant area of cross section, Ac involving circle or square or triangle. Findings: The thin sample limit (Regime 1) corresponds to samples with spatially invariant power absorption, whereas power absorption attenuates from exposed to unexposed faces for thick samples (Regime 4). In Regimes 2 and 3, the average power absorption non-monotonically varies with sample size or area of cross section (Ac) and a few maxima of average power occur for fixed values of Ac involving various shapes. The spatial characteristics of power and temperature have been critically analyzed for all cross sections at each regime for lossy samples. Triangular samples are found to exhibit occurrence of multiple heating fronts for large samples (Regimes 3 and 4). Practical implications: Length scales of samples of various shapes (circle, square and triangle) can be represented via Regimes 1-4. Regime 1 exhibits the identical heating rate for lateral and radial irradiations for any shapes of lossy samples. Regime 2 depicts that a larger heating rate with larger temperature non-uniformity can occur for square and triangular-Type 1 lossy sample during lateral irradiation. Regime 3 depicts that the penetration of heat at the core is larger for triangular samples compared to circle or square samples for lateral or radial irradiation. Regime 4 depicts that the penetration of heat is still larger for triangular samples compared to circular or square samples. Regimes 3 and 4 depict the occurrence of multiple heating fronts in triangular samples. In general, current analysis recommends the triangular samples which is also associated with larger values of temperature variation within samples. Originality/value: GFEM with generalized mesh generation for all geometries has been implemented. The dielectric samples of any shape are surrounded by the circular shaped air medium. The unified mesh generation within the sample connected with circular air medium has been demonstrated. The algorithm also demonstrates the implementation of various complex boundary conditions in residuals. The numerical results compare the heating patterns for all geometries involving identical areas. The thermal characteristics are shown with a few generalized trends on enhanced heating or targeted heating. The circle or square or triangle (Type 1 or Type 2) can be selected based on specific heating objectives for length scales within various regimes. [ABSTRACT FROM AUTHOR]

Purpose: This paper aims to propose a novel direct method for indefinite algebraic linear systems. It is well adapted for sparse linear systems, such as those of two-dimensional (2-D) finite elements problems, especially for coupled systems. Design/methodology/approach: The proposed method is developed on an example of an indefinite symmetric matrix. The algorithm of the method is given next, and a comparison between the numbers of operations required by the method and the Cholesky method is also given. Finally, an application on a magnetostatic problem for classical methods (Gauss and Cholesky) shows the relative efficiency of the proposed method. Findings: The proposed method can be used advantageously for 2-D finite elements in stepping methods without using a block decomposition of matrices. Research limitations/implications: This method is advantageous for direct linear solving for 2-D problems, but it is not recommended at this time for three-dimensional problems. Originality/value: The proposed method is the first direct solver for algebraic linear systems proposed since more than a half century. It is not limited for symmetric positive systems such as many of direct and iterative methods. [ABSTRACT FROM AUTHOR]

Purpose: This paper aims to improve the radial basis fuction mesh morphing method. During a shape optimization based on computational fluid dynamic (CFD) solvers, the mesh has to be changed. Two possible strategies are re-meshing or morphing. The morphing one is advantageous because it preserves the mesh connectivity, but it must be constrained. Design/methodology/approach: RBF mesh deformation is one of the most robust and accurate morphing method. Using a greedy algorithm, the computational cost of the method is reduced. To evaluate the morphing performances, a rib shape optimization is performed using the NSGA-II algorithm coupled to kriging metamodels based on CFD. The morphing method is then compared to a re-meshing strategy. Findings: The authors propose a method, based on Schur complement, to speed-up the greedy process. By using the information of the previous iteration, smaller linear systems are solved and time is saved. The optimization results highlight the interest of using a morphing-based metamodel regarding the resolution time and the accuracy of the interpolated solutions. Originality/value: A new method based on Schur complement is addressed to speed-up the greedy algorithm and successfully applied to a shape optimization. [ABSTRACT FROM AUTHOR]

Purpose: This paper aims to get the optimal controller parameters of fractional order proportional integral derivative (FOPID)/proportional integral derivative (PID) i.e. Kp, Ki, Kd, λ and µ for designing controller in automatic voltage regulator (AVR) system. Design/methodology/approach: A novel method is proposed to get the optimal controller parameters for designing controller in AVR system using improved Jaya algorithm (IJA). The time domain objective and regular integral error objectives are used to design the controller to estimate the performance of the AVR system based on optimal tuning FOPID/PID controller. Findings: The proposed method captures time domain objective of the FOPID/PID controller design and demonstrates effective transient response and better control action. The efficient tuning of FOPID controller results in high superiority of control efforts. Practical implications: The simulations of IJA-based FOPID/PID controller design method are performed in MatLab tool and compared with several methods in the recent state of the art and the same are observed to be robust for the AVR system. Originality/value: The developed optimal FOPID/PID controller tuning using IJA optimization method is totally a new approach for the AVR system in the literature. [ABSTRACT FROM AUTHOR]

Purpose: This paper aims to propose two parallel two-step finite element algorithms based on fully overlapping domain decomposition for solving the 2D/3D time-dependent natural convection problem. Design/methodology/approach: The first-order implicit Euler formula and second-order Crank–Nicolson formula are used to time discretization respectively. Each processor of the algorithms computes a stabilized solution in its own global composite mesh in parallel. These algorithms compute a nonlinear system for the velocity, pressure and temperature based on a lower-order element pair (P1b-P1-P1) and solve a linear approximation based on a higher-order element pair (P2-P1-P2) on the same mesh, which shows that the new algorithms have the same convergence rate as the two-step finite element methods. What is more, the stability analysis of the proposed algorithms is derived. Finally, numerical experiments are presented to demonstrate the efficacy and accuracy of the proposed algorithms. Findings: Finally, numerical experiments are presented to demonstrate the efficacy and accuracy of the proposed algorithms. Originality/value: The novel parallel two-step algorithms for incompressible natural convection problem are proposed. The rigorous analysis of the stability is given for the proposed parallel two-step algorithms. Extensive 2D/3D numerical tests demonstrate that the parallel two-step algorithms can deal with the incompressible natural convection problem for high Rayleigh number well. [ABSTRACT FROM AUTHOR]

Purpose: This research aims to focus on the problem of optimizing the layout of charging stations. Design/methodology/approach: The authors estimate the total number of charging stations by the number of existing gas stations using clustering by fast search-and-find of density peaks (CFSFDP) algorithm. Findings: This paper reveals the relationship between the distance and the population. Priority should be given to the short-distance and high-frequency travel charging needs in the city, followed by low frequency and travel, which can improve the use efficiency of the whole charging network. Originality/value: First, the total number of charging stations is estimated by the number of existing gas stations. This method can fully consider the growth potential of charging vehicles instead of the traditional cars. Besides, the cost-benefit method is proposed to explore the marginal coverage distance of the city's charging network and can be used to reveal the relationship between the distance and the population. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this paper is to propose a local parallel finite element algorithm based on fully overlapping domain decomposition technique to solve the incompressible magnetohydrodynamic equations. Design/methodology/approach: The algorithm uses a lower-order element pair to compute an initial approximation by the Oseen-type iteration and uses a higher-order element pair to solve a linear system in each processor. Findings: Besides, the convergence analysis of local parallel finite element algorithm is given. Finally, numerical experiments are presented to verify the efficiency of the proposed algorithm. Originality/value: Compared with the numerical solution of the common two-step method, this method is easy to realize and can produce a more accurate solution. And, this approach is executed in parallel, so it saves a lot of computational time. [ABSTRACT FROM AUTHOR]

Purpose The purpose of this paper is to examine the convergence, offered accuracy and efficiency of the bisectional adaptive frequency sampling (AFS) scheme combined with the Stöer-Bulirsch (SB) algorithm as a tool for supporting frequency-domain method-of-moments (MoM) in broadband electromagnetic (EM) simulations.Design/methodology/approach The AFS and SB procedures have been interfaced with the MoM code, and then, an extensive parametric study has been carried out to explore the performance of the numerical solution for the test problems of reconstructing frequency responses of the wire radiator and scatterer, respectively, over at least a decade bandwidth.Findings The results give evidence for the efficiency of the overall approach and its capability of constructing the approximation of multi-resonant responses with sharp resonant peaks from a substantially reduced number of EM samples (data points) compared to that of conventional uniform sampling.Originality/value Results of the study offer thorough insight into the performance of the AFS-SB technique, and the data given in this paper may be helpful in selecting the convergence criterion and the tolerance for the AFS-SB algorithm to achieve a possibly economical broadband simulation technique. [ABSTRACT FROM AUTHOR]

Purpose In this paper, a new structure for the permanent magnet hysteresis synchronous (PMHS) motor is introduced. Moreover, this paper aims to presents a new analytical method for modeling of a disc-type PMHS motor.Design/methodology/approach Because the hysteresis and permanent magnet motors have unique characteristics, a motor (the PMHS motor) with excellent performance features can be achieved by combining them. Choosing a disc-type slotless structure causes the major advantages of both motors to be preserved in the new motor. To analyze PMHS motor, mathematical equations are obtained by using Ampere’s circuital law, flux continuity law and Faraday’s law. Then the air-gap voltage and exciting current of the motor can be calculated. To implement this method, a new iterative algorithm is proposed. This algorithm consists of one-iteration loop for each input voltage to find the maximum flux density of the operational hysteresis loop of the motor.Findings Validity of the analytical approach is confirmed by experimental results. A reasonably close agreement between the two is shown and some outstanding performances of the PMHS motor are demonstrated.Originality/value A new structure for PMHS motor and also a new analytical method for performance prediction of this motor is presented. [ABSTRACT FROM AUTHOR]

Purpose The purpose of this paper is to propose a new algorithm for detection of chaos in oscillatory circuits. The algorithm is based on the wavelet transform.Design/methodology/approach The proposed detection is developed by using a specific measure obtained by averaging wavelet coefficients. This measure exhibits various values for chaotic and periodic states.Findings The proposed algorithm is applied to signals from autonomous systems such as the Chua’s oscillatory circuit, the Lorenz chaotic system and non-autonomous systems such as the Duffing oscillator. In addition, the detection is applied to sequences obtained from the logistic map. The results are compared to those obtained with a detrended fluctuation analysis and a time-frequency signal analysis based on detectors of chaotic states.Originality/value In this paper, a new algorithm is proposed for the detection of chaos from a single time series. The proposed technique is robust to the noise influence, having smaller calculation complexity with respect to the state-of-the-art techniques. It is suitable for real-time detection with delay that is about half of the window width. [ABSTRACT FROM AUTHOR]

Purpose Type-2 fuzzy sets became attractive in practice because of their footprint of uncertainty that gives them more degrees of freedom. This paper aims to use genetic algorithms (GAs) to design an interval Type-2 fuzzy logic system (IT2FLS) for the purpose of predicting bankruptcy.Design/methodology/approach The shape of type-2 membership functions, the parameters giving their spread and location in the fuzzy partitions and the set of fuzzy rules are evolved at the same time by encoding all together into the chromosome representation. The enhanced Karnik–Mendel algorithms are used for the centroid type-reduction and defuzzification stage. The performance in predicting bankruptcy is evaluated by benchmarking IT2FLSs against type-1 FLSs. The experimental setup consists of evolving 100 configurations for both the T1FLS and IT2FLS and comparing their in-sample and out-of-sample average accuracy.Findings The experiments confirm that representing and capturing uncertainty with more degrees of freedom is an important advantage. It is this extra potential of IT2FLSs that allows them to outperform T1FLS, especially in terms of generalization capability.Originality/value The strategy followed in this paper is to train an IT2FLS from scratch rather than tuning the parameters of an existing T1FLS. Because this leads to solving a mixed integer optimization problem, the GA-based approach is specifically designed and uses genetic operators that are most suited for such a case: tournament selection, extended Laplace crossover and power mutation. Finally, the trained IT2FLS is applied to bankruptcy prediction, and its generalization capability is compared with related techniques. [ABSTRACT FROM AUTHOR]

Purpose This paper aims to analyse the differences in financial performance portfolios between sustainable and non-sustainable firms through the use of portfolio theory and OptQuest algorithms from 2007 to 2013.Design/methodology/approach The sample consists of 1,078 firms from 15 Organisation for Economic Cooperation and Development countries. A maximisation weighted ratio is estimated by applying OptQuest algorithms to measure the portfolio performance considering a fuzzy Jensen’s alpha and the percentage of the portfolio’s performance that exceeds the market.Findings The results show a similar financial performance in sustainable portfolios (SP) and non-SP, but considering the uncertainty, the performance in sustainable firms was better than that of non-sustainable ones. Uncertainty was reduced, as it passed the beginning of the crisis from 2008-2009 to 2012-2013.Research limitations/implications The main limitation is the different assessments of sustainability indexes in each of the countries.Practical implications The results help investors assess their decisions in an uncertain economic environment and allocate their investment in not only financial terms but also social character.Social implications Countries with higher financial performances in SP show the efficiency in their legal environmental regulations. On the other hand, the degree of uncertainty is lower in the SP than non-SP, suggesting that sustainable firms in financial crisis could be more responsible in social claims such as good working conditions.Originality/value This study contributes to existing research in two ways. First, the paper studies corporate social responsibility by different continents and countries in an uncertain economic timespan. For this, the legal, cultural and socioeconomic divergences and convergences were explored. Second, the research presented an analysis of the financial performance differences between sustainable and non-SP by applying a hybrid methodology with fuzzy regression and OptQuest algorithms. [ABSTRACT FROM AUTHOR]

Purpose Every student knows Newton’s iteration method from a textbook, which is widely used in numerical simulation, what few may know is that its ancient Chinese partner, Ying Buzu Shu, in about second century BC has much advantages over Newton’s method. The purpose of this paper is to introduce the ancient Chinese algorithm and its modifications for numerical simulation.Design/methodology/approach An example is given to show that the ancient Chinese algorithm is insensitive to initial guess, while a fast convergence rate is predicted.Findings Two new algorithms, which are suitable for numerical simulation, are introduced by absorbing the advantages of the Newton iteration method and the ancient Chinese algorithm.Research limitations/implications This paper focuses on a single algebraic equation; however, it is easy to extend the theory to algebraic systems.Practical implications The Newton iteration method can be updated in numerical simulation.Originality/value The ancient Chinese algorithm is elucidated to have modern applications in various numerical methods. [ABSTRACT FROM AUTHOR]

Purpose Estimating the punching process’s impact on the operating parameters of an electrical motor is a special problem especially in the case of fractional power motors. The purpose of this paper is to discuss a method of numerical modelling that is useful for this case.Design/methodology/approach The proposed multi-physical FEM approach is based on using professional software in the process of modelling and determining the operating parameters of a low power motor. The basic elements of the approach are built FEM models for which the parameters characterising the damaged portions of the magnetic material were determined. The material properties of this zone were determined both by measurement and by a new analytical approach described in this paper.Findings The paper formulates the impact of punching on the operating parameters of a low power motor. Moreover, it formulates the analytical algorithm for the estimation of properties of material in damaged zones.Research limitations/implications Experimental verification will still be needed to check the model’s accuracy and applicability to various magnetic materials.Practical implications The paper provides an easy approach enabling the calculation of motor operating parameters and a simple and useful algorithm to estimate magnetic material properties in the damaged zone.Originality/value The analytical algorithm, as presented here, in conjunction with the measurement results is useful and applicable to estimating the magnetic material properties, which form the basis for accurate FEM calculation. [ABSTRACT FROM AUTHOR]

Purpose The purpose of this paper is to use the proposed algorithm for the fast adaptation of the antenna array radiation pattern on the particular scenario of the incoming signals. The fitness function to be minimized includes the precise estimation of signals’ arrival angles, setting the deep nulls in the directions of the interfering signal, the reduction of the main lobe’s width and the reduction of side lobes.Design/methodology/approach Unlike conventional adaptive algorithms, the proposed algorithm allows synthesis of radiation patterns in the case of a larger number of incident desired and interfering signals. The proposed method also reduces the width of the dead zone.Findings In this paper a comparison of the results obtained from the chaotic beamforming algorithm with the results obtained by using the Sequential Quadratic Programming method is presented.Originality/value The chaotic beamforming algorithm is proposed here. It is based on the optimization of the least mean square and on the variable step-size least mean square algorithms, using chaos theory for synthesis of the radiation pattern of the linear antenna array. [ABSTRACT FROM AUTHOR]

Purpose Ordinary differential equations (ODEs) are widely used in the engineering curriculum. They model a spectrum of interesting physical problems that arise in engineering disciplines. Studies of different types of ODEs are determined by engineering applications. Various techniques are used to solve practical differential equations problems. This paper aims to present a computational tool or a computer-assisted technique aimed at tackling ODEs. This method is usually not taught and/or not accessible to undergraduate students. The aim of this strategy is to help the readers to develop an effective and relatively novel problem-solving skill. Because of the drudgery of hand computations involved, the method requires the need to use computers packages. In this work, the successive differentiation method (SDM) for solving linear and nonlinear and homogeneous or non-homogeneous ODEs is presented. The algorithm uses the successive differentiation of any given ODE to determine the values of the function’s derivatives at a single point, mostly x = 0. The obtained values are used to construct the Taylor series of the solution of the examined ODE. The algorithm does not require any new assumption, hence handles the problem in a direct manner. The power of the method is emphasized by testing a variety of models with distinct orders, with constant and variable coefficients. Most of the symbolic and numerical computations can be carried out using computer algebra systems.Design/methodology/approach This study presents a computational tool or a computer-assisted technique aimed at tackling ODEs. This method is usually not taught and/or not accessible to undergraduate students. The aim of this strategy is to help the readers to develop an effective and relatively novel problem-solving skill. Because of the drudgery of hand computations involved, the method requires the need to use computers packages.Findings This method is applied to a variety of well-known equations, such as the Bernoulli equation, the Riccati equation, the Abel equation and the second-order Euler equation, some with constant and variable coefficients. SDM handles linear and nonlinear and homogeneous or nonhomogeneous ODEs in a direct manner without any need to restrictive conditions. The method works effectively to the Volterra integral equations, as will be discussed in a coming work.Originality/value The method can be extended to a wide range of engineering problems that are modeled by differential equations. The method is simple and novel and highly accurate. [ABSTRACT FROM AUTHOR]

Purpose The purpose of this paper is to present detailed algorithms for simulation of individual and group control of production wells in hydrocarbon reservoirs which are implemented in a finite volume-based reservoir simulator.Design/methodology/approach The algorithm for individual control is described for the multi-lateral multi-connection ones based on the multi-segment model considering cross-flow. Moreover, a general group control algorithm is proposed which can be coupled with any well model that can handle a constraint and returns the flow rates. The performance of oil production process based on the group control criteria is investigated and compared for various cases.Findings The proposed algorithm for group control of production wells is a non-optimization iterative scheme converging within a few number of iterations. The numerical results of many computer runs indicate that the nominal power of the production wells, in general, is the best group control criterion for the proposed algorithm. The production well group control with a proper criterion can generally improve the oil recovery process at negligible computational costs when compared with individual control of production wells.Research/limitations/implications Although the group control algorithm is implemented for both production and injection wells in the developed simulator, the numerical algorithm is here described only for production wells to provide more details.Practical/implications The proposed algorithm can be coupled with any well model providing the fluid flow rates and can be efficiently used for group control of production wells. In addition, the calculated flow rates of the production wells based on the group control algorithm can be used as candidate solutions for the optimizer in the simulation-optimization models. It may reduce the total number of iterations and consequently the computational cost of the simulation-optimization models for the well control problem.Originality/value A complete and detailed description of ingredients of an efficient well group control algorithm for the hydrocarbon reservoir is presented. Five group control criteria are extracted from the physical, geometrical and operating conditions of the wells/reservoir. These are the target rate, weighted potential, ultimate rate and introduced nominal power of the production wells. The performance of the group control of production wells with different group control criteria is compared in three different oil production scenarios from a black-oil and highly heterogeneous reservoir. [ABSTRACT FROM AUTHOR]

Purpose The purpose of this paper is to perform an optimal design of a single-phase permanent magnet brushless DC motor (SPBLDCM) by using efficiency of the motor as an objective function. In the design procedure of the motor, a cuckoo search (CS) algorithm is used as an optimization tool.Design/methodology/approach For the purpose of this research work, a computer program for optimal design of electrical machines based on the CS optimization has been developed. Based on the design characteristics of SPBLDCM, some of the motor parameters are chosen to be constant and others variable. A comparative analysis of the initial motor model and the CS model based on the value of the objective function, as well as the values of the optimization parameters, is performed and presented.Findings Based on the comparative data analysis of both motor models, it can be concluded that the main objective of the optimization is realized, and it is achieved by an improvement of the efficiency of the motor.Practical implications The optimal design approach of SPBLDCM presented in this research work can be also implemented on other electrical machines and devices using the same or even other objective functions.Originality/value An optimization technique using CS as an optimization tool has been developed and applied in the design procedure of SPBLDCM. According to the results, it can be concluded that the CS algorithm is a suitable tool for design optimization of SPBLDCM and electromagnetic devices in general. The quality of the CS model has been proved through the data analysis of the initial and optimized solution. The quality of the CS solution has been also proved by comparative analysis of the two motor models using FEM as a performance analysis tool. [ABSTRACT FROM AUTHOR]

Purpose The purpose of the paper is to propose some modifications to the SIMPLE (semi-implicit method for pressure-linked equations) algorithm. These modifications can ensure the numerical robustness and optimize computational efficiency. They remarkably promote the ability of the SIMPLE algorithm for incompressible DNS (direct numerical simulation) of multiscale problems, such as transitional flows and turbulent flows, by improving the properties of dispersion and dissipation.Design/methodology/approach The MDCD (minimized dispersion and controllable dissipation) scheme and MMIM (modified momentum interpolation method) are introduced. Six typical test cases are used to validate the modified algorithm, including the linear convective flow, lid-driven cavity flow, laminar boundary layer, Taylor vortex and DHIT (decaying homogenous isotropic turbulence). Particularly, a highly unsteady DNS of separated-flow transition in turbomachinery is precisely predicted by the modified algorithm.Findings The numerical examples show the distinct superiority of the modified algorithm in both internal flows and external flows. The advantages of the MDCD scheme and MMIM make the SIMPLE algorithm a promising method for DNS.Originality/value Some effective modifications to the SIMPLE algorithm are addressed. It is the first attempt to introduce the MDCD approach into the SIMPLE-type algorithms. The new algorithm is especially suitable for the incompressible DNS of convection-dominated flows. [ABSTRACT FROM AUTHOR]

Purpose – Phishing is one of the major challenges faced by the world of e-commerce today. Thanks to phishing attacks, billions of dollars has been lost by many companies and individuals. The global impact of phishing attacks will continue to be on the increase and thus a more efficient phishing detection technique is required. The purpose of this paper is to investigate and report the use of a nature inspired based-machine learning (ML) approach in classification of phishing e-mails. Design/methodology/approach – ML-based techniques have been shown to be efficient in detecting phishing attacks. In this paper, firefly algorithm (FFA) was integrated with support vector machine (SVM) with the primary aim of developing an improved phishing e-mail classifier (known as FFA_SVM), capable of accurately detecting new phishing patterns as they occur. From a data set consisting of 4,000 phishing and ham e-mails, a set of features, suitable for phishing e-mail detection, was extracted and used to construct the hybrid classifier. Findings – The FFA_SVM was applied to a data set consisting of up to 4,000 phishing and ham e-mails. Simulation experiments were performed to evaluate and compared the performance of the classifier. The tests yielded a classification accuracy of 99.94 percent, false positive rate of 0.06 percent and false negative rate of 0.04 percent. Originality/value – The hybrid algorithm has not been earlier apply, as in this work, to the classification and detection of phishing e-mail, to the best of the authors’ knowledge. [ABSTRACT FROM AUTHOR]

Purpose – Critical links in traffic networks are those who should be better protected because their removal has a significant impact on the whole network. So, the purpose of this paper is to identify the critical links of traffic networks. Design/methodology/approach – This paper proposes the definition of the critical link for an urban traffic network and establishes mathematical model for determining critical link considering the travellers’ heterogeneous risk-taking behavior. Moreover, in order to improve the computational efficiency, the impact area of a link is quantified, a partial network scan algorithm for identifying the critical link based on the impact area is put forward and the efficient paths-based assignment algorithm is adopted. Findings – The proposed algorithm can significantly reduce the search space for determining the most critical links in traffic network. Numerical results also demonstrate that the structure of efficient paths has significant impact on identifying the critical links. Originality/value – This paper identifies the critical links by using a bi-level programming approach and proposes a partial network scan algorithm for identifying critical links accounting for travellers’ heterogeneous risk-taking behavior. [ABSTRACT FROM AUTHOR]

Purpose – The purpose of this paper is to make the Bessel beamformer fully automatic when it is combined with root MUltiple SIgnal Classification (MUSIC) and is based on the array processing in the application of beamforming and direction of arrival algorithm for source position. The concept is analyzed for modified Bessel beamformer with root MUSIC to form a non-blind array processing technique which is then used to focus a beam toward a desired user and place nulls toward interferers for capacity improvement. Design/methodology/approach – The idea is manipulated for modified Bessel beamformer with root MUSIC relies on MATLAB software with the goal to obtain high efficiency in terms of signal recovery, directive gain by minimizing MSE and place nulls toward interferers. Findings – The finding of the analysis is presented in adaptive environment and provided in the tables. The paper shows that the presented method leads to superior results and can be used as a better alternative in many practical applications to avoid operator involvement. Research limitations/implications – The adaptive processes described in the paper are still limited to simulation due to non-availability of real system for testing. Practical implications – The paper can be extended to a next level by implementing the proposed algorithms in the real time environment using FPGA technology. Originality/value – This is the original work that can offer scientific contribution to signal processing community and may provide better results as an automatic beamformer. [ABSTRACT FROM AUTHOR]

Purpose – Collaborative recommender systems play a crucial role in providing personalized services to online consumers. Most online shopping sites and many other applications now use the collaborative recommender systems. The measurement of the similarity plays a fundamental role in collaborative recommender systems. Some of the most well-known similarity measures are: Pearson’s correlation coefficient, cosine similarity and mean squared differences. However, due to data sparsity, accuracy of the above similarity measures decreases, which makes the formation of inaccurate neighborhood, thereby resulting in poor recommendations. The purpose of this paper is to propose a novel similarity measure based on potential field. Design/methodology/approach – The proposed approach constructs a dense matrix: user-user potential matrix, and uses this matrix to compute potential similarities between users. Then the potential similarities are modified based on users’ preliminary neighborhoods, and k users with the highest modified similarity values are selected as the active user’s nearest neighbors. Compared to the rating matrix, the potential matrix is much denser. Thus, the sparsity problem can be efficiently alleviated. The similarity modification scheme considers the number of common neighbors of two users, which can further improve the accuracy of similarity computation. Findings – Experimental results show that the proposed approach is superior to the traditional similarity measures. Originality/value – The research highlights of this paper are as follows: the authors construct a dense matrix: user-user potential matrix, and use this matrix to compute potential similarities between users; the potential similarities are modified based on users’ preliminary neighborhoods, and k users with the highest modified similarity values are selected as the active user’s nearest neighbors; and the proposed approach performs better than the traditional similarity measures. The manuscript will be of particular interests to the scientists interested in recommender systems research as well as to readers interested in solution of related complex practical engineering problems. [ABSTRACT FROM AUTHOR]